Chaincode on Hyperledger Fabric 2.x Test Network (ARM64 Edition)

In this article, we will demonstrate the installation and execution of the Asset Transfer Basic chaincode (from Hyperledger Fabric samples) on our test network using the Docker images we build for the ARM64 platform from the source for Hyperledger Fabric 2.x.

Here is the link to the article:

Chaincode on Hyperledger Fabric 2.x Test Network

Enjoy πŸ˜‰ !!!

Setup Hyperledger Fabric 2.x Test Network (ARM64 Edition)

In this article, we will demonstrate the setup of the test network from Hyperledger Fabric samples using the Docker images we build for the ARM64 platform from the source for Hyperledger Fabric 2.x.

Here is the link to the article:

Setup Hyperledger Fabric 2.x Test Network

Enjoy πŸ˜‰ !!!

Building Docker Images for Hyperledger Fabric 2.x (ARM64 Edition)

Given that ARM based Single Board Computers (SBCs) are growing in popularity and perfect for building home lab clusters, did not see any official distribution for Hyperledger Fabric 2.x.

In this article, we will layout the steps to build the necessary Docker images from the source for Hyperledger Fabric 2.x.

Here is the link to the article:

Building Docker Images for Hyperledger Fabric 2.x

Enjoy πŸ˜‰ !!!

Linux Mint 21 MATE Edition Samba Share Gotcha

For those trying to share the Public folder using the Samba Share (via caja-share), you will encounter the following error:

net usershare error 355

To workaround it, execute the following command in a Terminal:

    • net usershare add Public $HOME/Public “” everyone:F guest_ok=y

To verify the command was successful, execute the following command in the Terminal:

    • net usershare info –long

Machine Learning – Support Vector Machines using Scikit-Learn

In this article series, we will get our hands dirty with Support Vector Machines (SVM) using Scikit-Learn. We will use the use the Heart Failure clinical records data set from UCI to predict death event.

Here is the link to the article:

Machine Learning – Support Vector Machines using Scikit-Learn

Enjoy πŸ™‚ !!!